Information services systems have been implemented since the beginning of telephony communications. For various reasons, and historically based on the need for directory assistance, telephony subscribers could call an information services system, request particular information, and receive the information. As communications evolve, the sophistication of the information services systems and the type of information provided with these systems has significantly increased. Currently, information services systems provide all types of information, from traditional directory numbers and addresses to driving directions and movie listings.
As the need for information services increases, information services providers have implemented automated systems that are capable of handling certain requests in a fully automated fashion, without requiring operator assistance, by utilizing technologies such as speech recognition, speech synthesis, recorded speech playback, and digit detection. Naturally, there are numerous reasons, such as varying accents, dialects, and languages, which prevent these automated systems from being able to properly respond to all requests. As such, the requests that are not recognized or otherwise handled properly may be sent to a human operator, who will interact with the caller and provide the requested information.
Given the significant cost savings associated with automation, there is a continuing need to provide more accurate and reliable automation. The primary hurdle in automation is the difficulty in recognizing speech due to the various languages, accents, dialects, and pronunciations of words that formulate the caller's request for information. At this time, the speech recognition engines in these information services automation systems are only updated periodically, and these updates are not necessarily based on actual use, but rather on general predictions involving speech recognition patterns. Further, there is no mechanism to provide feedback to the automation system based on actions taken by the operator after the automation system has failed. There is a need to provide feedback to the automation system based on the operator's interaction with the caller to improve speech recognition, and thus the ability to automate future requests in a more effective manner.